Semesterproject paper
Aurelia Möri, Lisa Wahlen
2023-07-04
Length of report (approx. 15000 char (incl. spaces, incl. References list, excl. Code listing), 20000 char max)
Introduction
Mountainbiking is a popular sport in Switzerland (Fischer et al., 2021), that raises both environmental and policy issues (Pröbstl-Haider et al., 2018). In order to better understand mountainbiking, this project takes a closer look at the movment of downhill mountainbiking. and be able to talk about these issues on an objective level, it could be of interest to find out more about mountainbiking from a spatial use and movement based perspective.
Mountain biking can be practiced on different surfaces (on or off-road), there is a preference for natural areas (Zajc & Berzelak, 2016).
movement data of interest. describing movement in GIScience In this project, we aim at filtering mountainbiking movement patterns in crowdsourced movement data according to specific movement criteria which should only apply to mountianbikers.
In this project, we aim at defining criteria that indicate mountainbiking movement patterns, and try to provide information about the characteristics of mountainbiking.
what are characteristics of mountainbiking? -> downhill (not uphill), in vegetated areas / trails (not on streets), within a certain speed range.
In order to filter the mountainbiking pattern, we defined three criteria with which we should be able to have a unique identifier. Those three criteria consist of the speed with which the person is moving, the groundtype on which the trajectory is laying and furthermore the steepness of the trajectory, which needs to be directed downhill. Using just one or two of the criteria will always still allow for other activities. Such that a trajectory placed on grass and in forests could still also be a hiker, which also applies to the downhill movement. The Speed of a mountainbiker is hard to define, but it is also not a unique identifier for this movement pattern.
Research Question
In this project we will work on the following two research questions:
How can speed, ground cover and downward motion be used to characterize the movement pattern of downhill mountainbiking?
Can I detect segments where mountainbiking occurred based on speed, groundcover and downward motion?
Are the chosen criteria applicable to other movement trajectories?
Data and Methods
Datasets
For the project, I used the movement trajectories that were created by Lisa Wahlen when going mountainbiking. The trajectories were recorded by using the GPS-tracking App posmo (Genossenschaft Posmo Schweiz, 2022) with a sampling rate of 10 seconds. We include 3 mountainbiking tours Lisa completed in the period from the 6th of May to the 18th of May 2023. The tours were recorded in Switzerland in the areas of Wiriehorn (2 tours) and Valbirse (1 tour).
For the assessment of the criteria that describe the movement pattern of mountain biking, we used the MOPUBE vector dataset providing the land cover types of the canton of Bern, using the version last updated on the 23.05.23 (Amt für Geoinformation des Kantons Bern, 2023). In addidtion, we worked with parts of the swiss digital terrain model swissALTI3D (Bundesamt für Landestopografie swisstopo, 2022). This elevation data is provided as raster in a resolution of 0.5 m in grids of 1 km2. We worked with extracts of the datasets, covering the spatial extent of the trajectories within the Canton of Bern.
We chose the tour Lisa made on the 18th of May in the Wiriehorn area (Wiriehorn 05-18) to define the characteristics of the biking movement pattern and tried to apply the criteria to the tour at Wiriehorn on the 7th of May (Wiriehorn 05-07) and the tour in Valbirse on the 6th of May for verification. The trajectories included the car ride from Solothurn to the biking location and back. A first visualisation of transport modes of the data revealed that the mountainbiking part of the trajectories were labelled by the posmo app as “Car”, “Bus”, “Other” - and sometimes almost correctly with “Bike”.
Wiriehorn trajectory of the 18th of May
Navigating to the south of the trajectory you’ll find the
mountainbiking part.
Wiriehorn trajectory of the 7th of May
Navigating to the south of the trajectory you’ll find the
mountainbiking part.
Valbirse trajectory of the 6th of May
Navigating to the northeast of the trajectory you’ll find the
mountainbiking part.
Preprocessing
All datasets of the trajectories were first converted to a georeferenced feature. Temporal outliers recorded the night before the trip started were removed, as well as unnecessary or redundant information about Lisa’s user ID, the weekday, or the place name.
Preprocessing Bodenbedeckung? in ArcGIS 50m buffer on both sides of the trajectory line
Preprocessing swissALTI3D? polygon extract during acquisition.
Methods
Three relevant criteria for mountainbiking are speed, downhill movement and ground cover (Quelle). For all three criteria I assessed the values and ranges fitting the mountainbiking pattern of the Wiriehorn 05-18 tour. Then I applied the criteria to the Wiriehorn 05-06 and the Valbirse tour.
Speed and segmentation
For every fix on the trajectory I calculated the average speed within the window of four neighboring points, similar to the moving window method of Laube & Purves (2011). The euclidean distance to the two points before and the two points after the fix was calculated and divided by the time difference between the fix and the two points before and after, respectively. Fixes where the speed calculation could not be completed because either the distance or the time between two points was 0, were regarded as static. On the Wiriehorn 05-18 tour, 80 points were labelled as static, and used for segmentation of the trajectory. They were located in places on the trajectory where little movement or a change in transport mode is plausible (e.g. at the bottom and the top of the cable car allmiried, somewhere in the middle of the downhill trail, at train stations in Solothurn). The segments were used to identify parts of the trajectory where Lisa was mountainbiking. The relevant segments were selected based on visual assessment of the movement parameter profile (Dodge et al. 2009) of the average speed (Figure below). I assumed that short segments and segments with high velocities are not biking.
However, the selected segments included the movement of the cable car Lisa took to get uphill to the trail start. To isolate the cable car and determine the relevant speed range for mounainbiking, the average speed distribution of the selected segments was calculated. The speed values that best characterized the movement of mountain biking were identified through a process of testing.
Ground cover
The MOPUBE dataset showed 22 ground cover types (see figure below). Knowing about the preference for natural contexts for mountainbiking (Zajc & Berzelak, 2016) I assume that Lisa rode on vegetated and/or natural groundcovers. Thus, every groundcover type seems suitable except for “Abbau, Deponie”, Bahn”, “Gebäude”, “Strasse, Weg”, “Trottoir”, “übrige befestigte” and “Verkehrsinsel”. We could argue that water bodies are not suitable as well, but depending on their size it is not impossible to cross such features when biking.